Find research datasets worth reusing

opencc-by-4.0Sep 2022View details →

3D models: the dynamics of the prehistoric communities located in the Mostiștea Valley and Danube Plain (between Oltenița and Călărași)

This dataset is part of a larger project on the dynamics of the prehistoric communities located in the Mostiștea Valley and Danube Plain (between Oltenița and Călărași), supervised by the ArchaeoSciences Division of the Research Institute of the University of Bucharest (ICUB)  and Kiel University (Germany), in partnership with HOGENT, University of Applied Sciences and Arts (Belgium), Museum of Bucharest, Museum of the Lower Danube Călărași, Museum of Gumelnița Civilization Oltenița, and "Vasile Pârvan" Institute of Archaeology (Romania), under the "Sultana School of Archaeology" initiative. Spatial data play a crucial role in archaeological research, and orthophotos, digital elevation models, and 3D models are frequently used for the mapping, documentation, and monitoring of archaeological sites. Thanks to the availability of compact and low-cost uncrewed airborne vehicles, the use of UAV-based photogrammetry is well matured in this field over the last two decades. More recently, compact airborne systems are also available that allow the recording of thermal data, multispectral data, and airborne laser scanning. For this project, various platforms and sensors are applied at the Chalcolithic archaeological sites in the Mostiștea Basin and Danube Valley (Southern Romania). By analyzing the performance of the systems and the resulting data, insight is given into the selection of the appropriate system for the right application. This analysis requires thorough knowledge of data acquisition and data processing as well. As both laser scanning and photogrammetry typically result in very large amounts of data, a special focus is also required on the storage and publication of the data. Hence, the objective of this project is to provide a full overview of various aspects of 3D data acquisition for UAV-based mapping. Based on the conclusions drawn in our related publications, it is stated that photogrammetry and laser scanning can result in data with similar geometrical properties when acquisition parameters are appropriately set. On the one hand, however, the used ALS-based system outperforms the photogrammetric platforms in terms of operational time and the area covered. On the other hand, conventional photogrammetry provides flexibility that might be required for very low-altitude flights, or emergency mapping. Furthermore, as the used ALS sensor only provides a geometrical representation of the topography, photogrammetric sensors are still required to obtain true color- or false color composites of the surface. Lastly, the variety of data, like pre- and post-rendered raster data, 3D models, and point clouds, requires the implementation of multiple methods for the online publication of data. Various client-side and server-side solutions are presented to make the data available for other researchers.

opencc-by-4.0Sep 2022View details →

Changes in the acoustic structure of Australian bird communities along a habitat complexity gradient

Avian vocalizations have evolved in response to a variety of abiotic and biotic selective pressures. While there is some support for signal convergence in similar habitats that is attributed to adaptation to the acoustic properties of the environment (the ‘acoustic adaptation hypothesis’, AAH), there is also evidence for character displacement as result of competition for signal space among coexisting species (the ‘acoustic niche partitioning hypothesis’). We explored the acoustic space of avian assemblages distributed along six different habitat types (from herbaceous habitats to warm rainforests) in south eastern Queensland, Australia. We employed three acoustic diversity indices (acoustic richness, evenness, and divergence) to characterize the signal space. In addition, we quantified the phylogenetic and morphological structure (in terms of both body mass and beak size) of each community. Acoustic parameters showed a moderately low phylogenetic signal, indicating labile evolution. Although, we did not find meaningful differences in acoustic diversity indices among habitat categories, there was a significant relationship between the regularity component (evenness) and vegetation height indicating that acoustic signals are more evenly distributed in dense habitats. After accounting for differences in species richness, the volume of acoustic space (i.e., acoustic richness) decreased as the level of phylogenetic and morphological resemblance among species in a given community increased. Additionally, we found a significantly negative relationship between acoustic divergence and divergence in body mass indicating that the less different species are in their body mass, the more different their songs are likely to be. This implies the existence of acoustic niche partitioning at community level. Overall, while we found mixed support for the AAH, our results suggest that community-level effects may play a role in structuring acoustic signals within avian communities in this region. This study shows that signal diversity estimated by diversity metrics of community ecology based on basic acoustic parameters can provide additional insight into the structure of animal vocalizations.

opencc-zeroSep 2022View details →

Data and code from: Functional rarity of plants in German hay meadows - patterns on the species level and mismatches with community species richness

Functional rarity (FR) - a feature combining a species' rarity with the distinctiveness of its traits - represents a promising tool to better understand the ecological importance of rare species and consequently to protect functional diversity more efficiently. Yet, we lack a systematic understanding of FR on both the species level (which species are functionally rare and why) and the community level (how is FR associated with biodiversity and environmental conditions). Here, we quantify FR for 218 plant species from German hay meadows on a local, regional, and national scale by combining data from 6500 vegetation relevés and 15 ecologically relevant traits. We investigate the association between rarity and trait distinctiveness on different spatial scales via correlation measures and show which traits lead to low or high trait distinctiveness via distance-based redundancy analysis. We test how species richness and FR are correlated and use boosted regression trees to determine environmental conditions driving species richness and FR. On the local scale, only rare species showed high trait distinctiveness while on larger spatial scales rare and common species showed high trait distinctiveness. As infrequent trait attributes (e.g., legumes, low clonality) led to higher trait distinctiveness, we argue that functionally rare species are either specialists or transients. While specialists occupy a particular niche in hay meadows leading to lower rarity on larger spatial scales, transients display distinct but maladaptive traits resulting in high rarity across all spatial scales. More functionally rare species than expected by chance occurred in species-poor communities indicating that they prefer environmental conditions differing from characteristic conditions of species-rich hay meadows. Finally, we argue that functionally rare species are not necessarily relevant for nature conservation, since many were transients from surrounding habitats. Yet, FR can facilitate our understanding of why species are rare in a habitat and under which conditions these species occur.

opencc-zeroSep 2022View details →

Geomorphology shapes relationships between animal communities and ecosystem function in large rivers

Understanding how the Earth's surface (i.e., 'nature's stage') influences connections between biodiversity and ecosystem function (BEF) is a central objective in ecology. Despite recent calls to examine these connections at multiple trophic levels and at more complex and realistic scales, little is known about how landscape structure shapes BEF relationships among animal communities in nature. We coupled high-resolution habitat mapping with extensive field sampling to quantify connections among the geophysical habitat templet, invertebrate assemblages, and secondary production in two large North American riverscapes. Patterns of sediment size governed invertebrate assemblage structure, with particularly strong effects on composition, richness, and taxonomic and functional diversity. These relationships propagated to drive positive relationships between biodiversity and secondary production that were modified by scale, context-dependencies, and anthropogenic modification. Finally, leveraging spatially explicit descriptions of geophysical and biological properties, we uncovered distinct and nested spatial scales of biodiversity and secondary production, and suggest that multiple geophysical processes simultaneously influence these patterns at different scales. Together, our findings advance our understanding of relationships between the physical templet and patterns of BEF, and help to predict how perturbations to the Earth's surface may propagate to influence biodiversity and energy flux through food webs.

opencc-by-4.0Mar 2022View details →

Genome of the isolates: Enhanced cultured diversity of the mouse gut microbiota enables custom-made synthetic communities

The draft genome of the isolates in Mouse Intestinal Bacteria Collection (miBC)   Microbiome research is hampered by the fact that many bacteria are still unknown and by the lack of publicly available isolates. Fundamental and clinical research is in need of comprehensive and well-curated repositories of cultured bacteria from the intestine of mammalian hosts. Due to host-specific features of the gut microbiota, it is sound to establish collections of isolates from single host species. Hence, this project established a collection of bacterial strains isolated from the intestine of mice. The original version of the collection published in 2016 (Lagkouvardos, et. al. 2016. Nat. Microbiol.). was doubled by the addition of 112 strains, representing a total of 141 species across 6 phyla and 35 families for the entire collection. As we aimed to create a well-curated resource, all bacterial species within miBC have been taxonomically described and are publicly available.

Examining the diversity, stability and functioning of marine fish communities across a latitudinal gradient

Aim: As anthropogenic stressors on the biosphere intensify, understanding how communities respond to disturbances is critical. Biodiversity is often thought to promote the stability of communities over time and enhance ecosystem functioning. However, results have been inconsistent, and the multifaceted linkages among diversity, stability, and functioning under acute disturbances remain poorly understood. We experimentally tested the responses of marine fish communities to disturbance (i.e., acute habitat loss) across a diversity gradient spanning 35º degrees of latitude in the western Atlantic Ocean to assess the diversity-stability relationship and the interplay between diversity, stability, and fish biomass recovery (as a proxy for function) in marine fish communities. Location: Western Atlantic Ocean (Maine, Massachusetts, North Carolina, Florida [USA], Belize, and Panama). Time period: 2016 – 2017 Major taxa studied: Small, bottom-dwelling ('cryptobenthic') fishes Results: Diversity showed a negative effect on community stability at both the regional (across docks) and local (within docks) scales. Similarly, local diversity was negatively correlated with ecosystem function. These effects are exacerbated by the habitat loss imposed via our experimental treatment. Main conclusions: Our results suggest that habitat loss may more intensively re-shuffle diverse, tropical communities, which impacts biomass recovery, our proxy of functioning. Contrary to ecological theory, in small-bodied, benthos-associated vertebrate communities, biodiversity may neither promote stability nor functioning, suggesting that human disturbances may be particularly impactful in tropical, high-diversity ecosystems.

spectre: An R package to estimate spatially-explicit community composition using sparse data

An understanding of how biodiversity is distributed across space is key to much of ecology and conservation. Many predictive modelling approaches have been developed to estimate the distribution of biodiversity over various spatial scales. Community modelling techniques may offer many benefits over single-species modelling. However, techniques capable of estimating precise species makeups of communities are highly data intensive and thus often limited in their applicability. Here we present an R package, spectre, which can predict regional community composition at a fine spatial resolution using only sparsely sampled biological data. The package can predict the presence and absence of all species in an area, both known and unknown, at the sample site scale. Underlying the spectre package is a min-conflicts optimisation algorithm that predicts species' presences and absences throughout an area using estimates of α-, β-, and γ-diversity. We demonstrate the utility of the spectre package using a spatially-explicit simulated ecosystem to assess the accuracy of the package's results. spectre offers a simple-to-use tool with which to accurately predict community compositions across varying scales, facilitating further research and knowledge acquisition into this fundamental aspect of ecology.

Fig. 4 in Spatial Heterogeneity Of Steppe Bird Community In The Azov-Black Sea Enclave Of The European Dry-Steppe Zone (Southern Ukraine)

Fig. 4. Distribution of steppe dominants, co-dominants and rare steppe species (Black Book of Ukraine, 2009) by subregions of the dry-steppe enclave: * the largest areas in most count squares are covered by large bodies of water (seas and their bays, limans, the Dnipro floodplain).

Fig. 1 in Spatial Heterogeneity Of Steppe Bird Community In The Azov-Black Sea Enclave Of The European Dry-Steppe Zone (Southern Ukraine)

Fig. 1. Division of the Azov-Black Sea dry-steppe enclave into count squares of 10x10 km and subregions: 1 — RB Prychornomoria, 2 — Lower Dnipro, 3 — LB Prychornomoria, 4 — N Prysyvashshia, 5 — NW Pryazovia, 6 — Syvash, 7 — Western Crimea, 8 — Central Crimea, 9 —Kerch Peninsula, 10 — Foothills.

Fig. 2 in Spatial Heterogeneity Of Steppe Bird Community In The Azov-Black Sea Enclave Of The European Dry-Steppe Zone (Southern Ukraine)

Fig. 2. Similarity of subregions of the dry-steppe enclave in the number of all steppe bird species: 1 — RB Prychornomoria, 2 — Lower Dnipro, 3 — LB Prychornomoria, 4 — N Prysyvashshia, 5 — NW Pryazovia, 6 — Syvash, 7 — Western Crimea, 8 — Central Crimea, 9 —Kerch Peninsula, 10 — Foothills.

Fig. 3 in Spatial Heterogeneity Of Steppe Bird Community In The Azov-Black Sea Enclave Of The European Dry-Steppe Zone (Southern Ukraine)

Fig. 3. Similarity of subregions of the dry-steppe enclave in the number of rare steppe bird species: 1 — RB Prychornomoria, 2 — Lower Dnipro, 3 — LB Prychornomoria, 4 — N Prysyvashshia, 5 — NW Pryazovia, 6 — Syvash, 7 — Western Crimea, 8 — Central Crimea, 9 —Kerch Peninsula, 10 — Foothills.

Research Software Communities Global South

The Research Software Alliance's (ReSA) mission is to bring research software communities together to collaborate on the advancement of research software. Given the ReSA mission, it is important to understand the landscape of communities involved with research software. In 2020, ReSA completed an initial exercise to scope the international research software community landscape. This work was reported by ReSA's Software Landscape Analysis task force via a <a href="https://www.researchsoft.org/blog/2020-03/">blog post</a>. The majority of the communities in the previous analysis represented the global north. To improve the extent of this landscape analysis, ReSA announced a paid opportunity for short-term contractors located in <a href="https://www.researchsoft.org/2022-mapping/">the global south</a> to collect data on communities and funders in their region in early 2022. This document describes how the work was undertaken, a summary of findings, the gaps and opportunities perceived by the data collectors and some highlights. This work identified 126 organisations and communities and 62  funder bodies that support research software in the global south. Their main activities are connecting people, training, and networking, and support through research grants.   To add to this communities list please fill in the following form <a href="https://forms.gle/KJE9vkBnM6vhh7cEA">https://forms.gle/KJE9vkBnM6vhh7cEA</a>

opencc-zeroDec 2021View details →

Deciphering the interactions between plant species and their main fungal root pathogens in mixed grassland communities

1. Plant diversity can reduce the risk of plant disease, but positive, and neutral effects have also been reported. These contrasting relationships suggest that plant community composition, rather than diversity per se, affects disease risk. Here, we investigated how diversity and composition of plant communities drive root-associated pathogen accumulation belowground. 2. In a temperate grassland biodiversity experiment, containing 16 plant species (forbs and grasses), we determined the abundance of root-associated fungal pathogens in individual plant species growing in monocultures and in 4-species mixtures through Illumina MiSeq amplicon sequencing. 3. In the plant monocultures, we identified three major fungal pathogens that differed in host range: Paraphoma chrysanthemicola, associated with roots of forb species of the Asteraceae family, Slopeiomyces cylindrosporus, associated with grass species, and Rhizoctonia solani, associated with multiple forb and grass species. In mixtures, there was no significant reduction in relative abundance of these pathogens in their host species as compared to monocultures. However, in mixtures, there was a significant increase in relative abundance of each pathogen in several non-host and host plant species. Across mixtures, plant community composition affected pathogen relative abundance in individual plant species. This effect was driven by the presence of a particular neighbouring plant species (depending on the pathogen), rather than functional group composition (i.e. grass/forb ratio) or averaged pathogen pressure (based on monocultures) of all neighbours. Specifically, the presence of neighbour host species Achillea millefolium significantly increased P. chrysanthemicola, but decreased R. solani relative abundance in several host and non-host plant species in mixtures. 4. Synthesis: Our results indicate that interactions between different plant species – both host and non-hosts – and fungal pathogens underlie effects of plant diversity on root pathogen abundance. Non-host species may act as pathogen reservoirs in diverse plant communities, as they harboured certain pathogens in mixtures, but not in monocultures. Additionally, particular host species can strongly affect pathogen abundance in other (host and non-host) plant species in plant mixtures, suggesting clear effects of species identity in the diversity-disease relationship. Belowground disease risk thus depends on plant community composition rather than diversity per se, via specific interactions between plant species and their root-associated pathogens.

Assessing the importance of interspecific interactions in the evolution of microbial communities

These data and script are related to the article entitled "Assessing the importance of interspecific interactions in the evolution of microbial communities". This study reports the results of an experiment that aimed at understanding the role of interactions between bacterial species in the evolutionary responses of bacterial communities. The phenotype (optical density) of eight communities composed of two bacterial strains was assessed before and after an experimental evolution of five months (with a transfer each 3.5 days) and compared to the phenotype of communities rebuilt from the same strains that evolved in isolation. The phenotype of the bacterial strains of the study grown in isolation under the three evolutionary treatments (ancestor, evolved in isolation, evolved in community) was also assessed. All the data and codes needed to reproduce the figures and tables presented in the manuscript are provided.

Community level phylogenetic diversity does not differ between rare and common lineages across tallgrass prairies in northern Great Plains

In some cases, rare lineages provide resistance to invasions, serve as keystone species, and contribute unique functional or phylogenetic diversity to their communities. In other cases, rare species may be functionally redundant with common species and do not significantly contribute to phylogenetic diversity. How rare and common species coexist and contribute to local species pools may depend upon attributes of their communities and remains an open question in ecology. Niche differentiation has served as an explanation for species coexistence, and phylogenetic relatedness provides a means to approximate how ecologically similar species are to each other. To explore the contribution of rare species to community phylogenetic diversity, we sampled twenty-one plant communities across the Prairie Coteau ecoregion, home of the largest tracts of untilled northern tallgrass prairie and of high conservation concern. We used breakpoint analysis through iterative addition of less abundant species to the phylogenetic tree for each community. We also assessed the phylogenetic signal of abundance classes using Blomberg's K statistic and calculated the phylogenetic similarity between rare and common species using a phylogenetic beta diversity metric (Dnn). To estimate the phylogenetic structuring of these prairie communities, we calculated two common metrics that capture evolutionary relatedness between species (MPD, and MNTD) and examine the correlation between these metrics and species richness. Overall, we found rare species do not contribute higher levels of phylogenetic diversity than more common species in the Prairie Coteau ecoregion. Eight of 21 communities had significant breakpoints, where the addition of a less common species resulted in a shift in phylogenetic diversity, with only four communities having an increasing trend for the rarest species. Phylogenetic signal for abundance was low and unsignificant across 18 communities, while four sites did show significant low phylogenetic signal. We additionally found our communities had lower phylogenetic diversity than expected from the regional species pool. Finally, we found weak to no correlation when using MPD and MNTD. Our results indicate niche differentiation does not explain rare species persistence in tallgrass prairies. We found species were more closely related than expected from random community assembly, suggesting high functional redundancy within this system. This is promising for the long term viability of this ecosystem, but only insofar as enough species remain in the system to create redundancy. With ongoing biodiversity loss, it is essential we understand the role rare species play in their communities. Phylogenetic diversity could be an important tool for researchers and managers to utilize for conservation of critically threatened systems such as tallgrass prairies.

Inflation Reduction Act Energy Communities

The Inflation Reduction Act of 2022 (IRA) became law on August 8, 2022. Under the law, new qualifying renewable and/or carbon-free electricity generation projects constructed in certain areas of the US, called energy communities, are eligible for bonus worth an additional 10% to the value of the production tax credit or a 10 percentage point increase in the value of the investment tax credit. The IRA does not explicitly map or list these specific communities. Instead, eligible communities are defined by a series of qualifications: <ol> <li>a brownfield site,</li> <li>a metropolitan statistical area (MSA) or non-metropolitan statistical area with either (a) 0.17% or greater employment or (b) 25% or greater local tax revenues related to the extraction, processing, transport, or storage of coal, oil, or natural gas; and an unemployment rate at or above the national average for the previous year, or</li> <li>a census tract containing or adjacent to (a) a coal mine closed after December 31, 1999 or (b) a coal-fired electric generating unit retired after December 31, 2009.</li> </ol> These maps and data layers contain GIS data for coal mines, coal-fired power plants, fossil energy related employment, and brownfield sites. Each record represents a point, tract or metropolitan statistical area and non-metropolitan statistical area with attributes including plant type, operating information, GEOID, etc. The input data used includes: <ol> <li>Brownfields – Source: <a href="https://www.epa.gov/frs/geospatial-data-download-service">EPA</a>. No analysis was performed on this data layer. However, tract polygon layers have a column denoting brownfield presence (0 for no brownfield site, 1 if the tract contains a brownfield somewhere within the polygon).</li> <li>Eligible Employment MSAs (“Final_Employment_Qualifying_MSAs”) – Source: US Census <a href="https://www.census.gov/programs-surveys/cbp.html">County Business Patterns</a>. MSAs and non-MSA regions with employment over 0.17% in the fossil fuel industry (defined here as NAICS codes 211, 2121, 213, 23712, 324, 4247, and 486) and unemployment greater than or equal to 3.9% (the average national unemployment rate in 2021, according to the Bureau of Labor Statistics).</li> </ol> --Possibly Eligible MSAs (“FossilFuel_Employment_Qualifying_MSAs”) are MSA and non-MSA regions that meet or exceed the 0.17% employment in the fossil fuel industry threshold but do not exceed the unemployment threshold. --Relevant columns include:         a) SUM_nhgis0: Total employment in 2020.         b) SUM_nhgis1: Total unemployment in 2020.         c) P_Unemp: Percent unemployment in 2020.         d) Q_Unemp: Boolean column indicating if the MSA or non-MSA’s unemployment rate is at or above the national average of 3.9%.         e) FF_Qual: Boolean column indicating if the MSA or non-MSA had employment in the fossil fuel industry at or above 0.17% in the past 11 years.         f) final_Qual: Boolean column indicating if an MSA or non-MSA qualifies for both unemployment rate and fossil fuel employment under the IRA. <ol> <li>Retired Power Plants – Source: EIA via <a href="https://hifld-geoplatform.opendata.arcgis.com/maps/ee0263bd105d41599be22d46107341c3/about">HFLID</a>. Qualifying power plants were selected by use of coal in at least one generator, and if they were retired (RET_DATE) on or after January 1, 2010. This data goes through December 2021.</li> </ol> --Adjacent tract data was derived by Cecelia Isaac using ESRI ArcGIS Pro. <ol> <li>Abandoned Coal Mines – Source: <a href="https://www.msha.gov/mine-data-retrieval-system">MSHA</a>. Mines labeled “Abandoned”, “Abandoned and Sealed” or “NonProducing” between January 1, 2000 and September 2022.</li> </ol> --Adjacent tract data was derived by Cecelia Isaac using ESRI ArcGIS Pro. 5) US State Borders– Source: <a href="https://data2.nhgis.org/main">IPUMS NHGIS</a>.   Also included here are polygon shapefiles for Onshore <a href="https://zenodo.org/record/5021146#.Y0XbRnbMK39">Wind and Solar Candidate Project Areas</a> from <a href="https://repeatproject.org/">Princeton REPEAT</a>. These files have been updated to include columns related to the energy communities. New columns include: <ol> <li>CoalPlantTract: Boolean column indicating if the CPA is within a tract that qualifies because of a retired coal plant.</li> <li>CoalMineTract: Boolean column indicating if the CPA is within a tract that qualifies because of a closed coal mine.</li> <li>FossilFuelEmp: Boolean column indicating if the CPA is within an MSA or non-MSA with greater than or equal to 0.17% employment in the fossil fuel industry.</li> <li>UnempQualification: Boolean column indicating if the CPA is within an MSA or non-MSA with greater than or equal to 0.17% employment in the fossil fuel industry.</li> <li>MSA_non_to: The code of the MSA or non-MSA area that contains the CPA.</li> <li>P_Unemp: The percent unemployment of the MSA or non-MSA that contains the CPA in 2021.</li> </ol>

Biom files of bacterial rhizosphere communities from two pioneer species, Brachystegia boehmii and B. spiciformis

In this repository, you will find a mapping file of all samples and a biom table with all operational taxonomy units allowing the analyses of the bacterial rhizosphere communities.

Diversity and composition of macroinvertebrate communities in a rare inland salt marsh

Inland salt marshes are rare habitats in the Great Lakes region of North America, formed on salt deposits from the Silurian period. These patchy habitats are abiotically stressful for the freshwater invertebrates that live there, and provide an opportunity to study the relationship between stress and diversity. We used morphological and COI metabarcoding data to assess changes in diversity and composition across both space (a transect from the salt seep to an adjacent freshwater area) and time (three sampling seasons). Richness was significantly lower at the seep site with both datatypes, while metabarcoding data additionally showed reduced richness at the freshwater transect end, consistent with a pattern where intermediate levels of stress show higher diversity. We found complementary, rather than redundant, patterns of community composition using the two datatypes: not all taxa were equally sequenced with the metabarcoding protocol. We identified taxa that are abundant at the salt seep of the marsh, including biting midges (Culicoides) and ostracods (Heterocypris). We conclude that (as found in other studies) molecular and morphological work should be used in tandem to identify the biodiversity in this rare habitat. Additionally, salinity may be a driver of community membership in this system, though further ecological research is needed to rule out alternate hypotheses.

Different facets of bacterial and fungal communities drive soil multifunctionality in grasslands spanning a 3,500 km transect

1. Soil microbial communities are essential in regulating ecosystem functions and services. However, the importance of bacterial and fungal communities as predictors of multiple soil functions (i.e., soil multifunctionality) in grassland ecosystems has not been studied systematically. 2. Here, we measured soil microbial diversity, community composition, biomass, and multiple soil functions of 41 sites in five grassland ecosystems spanning a 3,500 km northeast–southwest transect. The random forest algorithm was adopted to determine the importance of geographical location, climatic, altitude, edaphic, plant, and microbial predictors in driving a proxy of soil multifunctionality (seven soil functions in this study). Moreover, structural equation models (SEMs) were employed to examine the direct and indirect effects of those predictors on soil multifunctionality. 3. Our results demonstrated that soil multifunctionality was positively driven by soil fungal diversity but not by bacterial diversity. Fungal phylogenetic diversity (presence of different evolutionary lineages) showed stronger positive relationships with soil multifunctionality than taxonomic diversity (richness of species). Dominant bacterial taxa, particularly of phyla Actinobacteria and Proteobacteria, were positively associated with soil multifunctionality, while none of the fungal taxa were found to regulate soil multifunctionality. Furthermore, both fungal and bacterial biomass had significant effects on soil multifunctionality, while the effect of microbial biomass was weaker than that of fungal diversity and bacterial taxa. Importantly, the direct positive effects of soil fungal diversity, dominant bacterial taxa, and fungal and bacterial biomass were maintained after accounting for multiple predictors in grassland ecosystems. 4. This study provided strong empirical evidence that soil multifunctionality was driven by different facets of the bacterial and fungal communities in the grassland ecosystems. Our results also highlighted that any loss of fungal diversity, dominant bacterial taxa and microbial biomass might reduce soil multifunctionality, exacerbating ecosystem functions and services such as soil fertility, primary production, and climate mitigation in grassland ecosystems.

Data for: Soil legacy effects of plants and drought on aboveground insects in native and range-expanding plant communities

Soils contain biotic and abiotic legacies of previous conditions that may influence plant community biomass and associated aboveground biodiversity. However, little is known about the relative strengths and interactions of the various belowground legacies on aboveground plant-insect interactions. We used an outdoor mesocosm experiment to investigate the belowground legacy effects of range-expanding versus native plants, extreme drought, and their interactions on plants, aphids, and pollinators. We show that plant biomass was influenced more strongly by the previous plant community than by a previous summer drought. Plant communities consisted of four congeneric pairs of natives and range expanders, and their responses were not unanimous. Legacy effects affected the abundance of aphids more strongly than pollinators. We conclude that historical climate warming-induced plant latitudinal range expansion and extreme drought contingencies can be contained as soil 'memories' that influence plant performance and aboveground community interactions in the next growing season.